NumPy for Data Science – Part 1

What is NumPy Array? An array is a grid of values and it contains information about the raw data, how to locate an element, and how to interpret an element. Numpy vs Python List Advantages of using NumPy Arrays over Python List: Let’s look at the example of NumPy Array and Python List. Importance of…

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Restaurant Recommendation System using Machine Learning

In this article we are going to discuss about the Restaurant Recommendation System. it is an application that recommends similar restaurants to a customer according to the customer’s taste. We will learn how to build a restaurant recommendation system. This article will take you through how to build a restaurant recommendation system using Machine Learning.…

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Hotel Sentiment Analysis using NLP

Whenever we are trying to find hotels for vacation or travel, we always prefer a hotel known for its services. The simplest way to find out whether a hotel is right for you or not is to find out what people are saying about the hotel who have stayed there before. Now it’s very difficult…

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Difference between Pandas .at and .iat Function

.at The .at and .iat index accessors are analogous to .loc and .iloc. The difference being that they will return a numpy.ndarray when pulling out a duplicate value, whereas .loc and .iloc return a Series: .iat .iat is similar to [] indexing. Because it tries to support both positional and label based indexing, I advise…

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Top 10 Pandas Functions

1 – To Read CSV and Excel files. These Functions will be used in almost every Project, They are used to read a CSV or an excel file to pandas DataFrame format. 2 – Columns Function. When we have a big dataset with many columns it will be difficult to see all columns, hence we…

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Difference between Pandas .iloc and .loc function

The optimized data access methods are accessed by indexing off of the .loc and .iloc attributes. These two attributes allow label-based and position-based indexing respectively. When we perform an index operation on the .iloc attribute, it does lookup based on index position (in this case pandas behaves similar to a Python list). DataFrame operation: .loc…

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Hierarchical clustering for Machine Learning

Hierarchical clustering is another unsupervised machine learning algorithm, which is used to group the unlabeled datasets into a cluster. Hierarchical Clustering creates clusters in a hierarchical tree-like structure (also called a Dendogram) as it creates a subset of similar data in a tree-like structure in which the root node corresponds to the entire data, and…

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Difference between Data Science and Machine Learning

Data Science Data science is a field that studies data and how to extract meaning from it, using a series of methods, algorithms, systems, and tools to extract insights from structured and unstructured and unstructured data. That knowledge then gets applied to business, government, and other bodies to help drive profits, innovate products and services…

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Difference between Data Scientist and Data Analyst

What are their skills? Data Analyst Data Mining Data Warehousing Math, Statistics Tableau and data visualization SQL Business Intelligence Advanced Excel skills Data Scientist Data Mining Data Warehousing Math, Statistics, Computer Science Tableau and Data Visualization/Storytelling Python, R, JAVA, Scala, SQL, Matlab, Pig Economics Big Data/Hadoop Machine Learning Educational requirements Data Analyst Foundational math, statistics…

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Difference between Data Scientist and Data Engineer

What do they do? Data Engineers Data Engineers design, build, test, integrate, and optimize data collected from multiple sources. They use Big Data tools and technologies to construct free-flowing data pipelines that facilitate real-time analytics applications on complex data. Data Engineers also write complex queries to improve data accessibility. Data Scientist Data Scientists are more…

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Difference between Big Data and Data Science

Big Data Hugh volumes of data which cannot be handled using traditional database programming. Characterized by volume, variety, and velocity. Data Science A data-focused on scientific activity. Approaches to process big data. Harnesses the potential of big data for business decisions. Similar to data mining. Concept Big Data Diverse data types generated from multiple data…

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Credit Card Fraud Detection using Machine Learning

As we’re moving towards the digital world — cybersecurity is getting a critical part of our life. When we talk about security in digital life also the main challenge is to find the abnormal activity. When we make any transaction while buying any product online — a good amount of people prefer credit cards. The…

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